Much weaker than Stanford offerings. Strange buildup of topics for a breezy, but not particular accurate understanding. For example: multiple layers of a neural network is introduced before multiple category classification. Transfer learning is introduced incorrectly. The matrix representation of multiple features of an example with multiple examples is introduced very late in the course. The instructor is conscientious and seemingly knows the material despite using non-standard terminology. One wonders if he is primarily a teacher/researcher and rarely a practitioner. One wonders if Duke is a leader in machine learning research.

This was a really great course for understanding the basics of machine learning through a lot of simple but relevant, real world examples.

Excellent course. Concepts such as gradient descent and convolutions as they pertain to neural networks are explained without going into the mathematical details but, in my opinion, are explained more intuitively and better, as compared to most other courses. The course does include some ungraded Jupyter notebooks exemplifying key elements of deep learning networks. Highly recommended to 'cement' understanding of neural networks.

Great course ! Pr Carin is clear enough to make you understand complex concepts like LSTM. The Math, calculus, algenra and prob are not too difficult. I enjoyed to follow this course ! To conclude a good introduction to ML to make you go deeper into the subject

It was great to touch new professional area and to understand its fundamentals. The course gives a broad view on machine learning, so I think now I really understand, what the machine learning is and how to use it in my work and even my political investigations.

Very good introductory course ,very well designed and professors explaination is very easy to understand .Go for it guys !

Happy learning !!!!

Sonic Somanna PK

I liked the pace and the tensor flow applications. This should be upgraded to TF 2.0 at some point. Also, I would've appreciated some GAN material.

I like this introductory course, very good one to start to learn machine learning. I will definitely continue studying and re-watch the videos.

Very Good course explaining the theoretical concepts related to deep learning . Thank you

A very fine tuned Course,used as a warm up course for deep learning,highly recommended

Great course for beginners, did a lot to fill in the gaps in my knowledge. There could be a little more help with the actual coding parts of the project, the work done in ipython notebook is largely self-taught.

The course is a good balance between learning key concepts and doing coding, the coding being optional. The phrasing of quiz questions and answers were sometimes confusing.

GOOD COURSE

I was an engineering major at Duke, but never took any sort of computer science/machine learning classes because I didn't have time. This class was super straight forward. Everything just made sense. I don't know how to say it other than that. It was great to see how much of the math and signal processing things I learned could be applied to something like machine learning. Before this class, I had no clue what machine learning was, and now I feel like I understand the main gist and the basis for all of the math behind it.

Really enjoyed the course - it was a bit heavy and required getting used to (also this was my first time doing a course online) but the course has a nice rhythm and it was excellent once i got the hang of it. Very useful course to get an insight into the world of Machine Learning and to increase curiosity and interest.

I have a background in pathology and I wanted to understand how machine learning works so that I can take an active part in the changes within my field and understand what is happening. This course was an amazing experience of learning, for someone like me with no background in calculus or linear algebra.

From zero background in Machine Learning to average in Machine Learning. I feel proud of myself, the journey has not been easy, I know with time and determination I shall get there, thank you Coursera for this privilege, I am grateful.

This course is an eye opener for anyone who wants to step or learn about Machine Learning. It provides various scenarios and the steps which you can apply to current real world problems.

This course is a must for all the beginners.

It is one of the very required course for beginners in ML, The problem is that it lacks in its python implementation. If there is the python implementation of this course then no other course is better than this one

It's really an amazing field to learn new things and from institute is like Amazing to me I've learnt more ...it's not at all boring and we'll will be excited for future experience with you 💯

Very good introductory course, I highly recommend it to anyone looking to get a flavour of the methods behind the recent advances in AI without going into super-technical details.

This course give a good introduction toward machine learning and AI. someone who wants to pursue his/her career in ML and AI in future this course would definitely help him/her

I have learned the basics concepts of CNN, RNN and other concepts may be used in Machine Learning. Instructor presents in a very simple way. ***** to Instructor

Very good course , good teaching method and easy to understand the lessons. I recommend for the beginners in Machine Learning.

with thanks ... Jithesh N V

An excellent course for a first pass at machine/deep learning. It will help you get what you need to look at other sources and understand them more.